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Record W2071228216 · doi:10.5539/mas.v8n6p258

A Novel of Suspended Plate Compact Antenna Design for 2.4 GHz Applications

2014· article· en· W2071228216 on OpenAlexvenueno aff
Muhammad Abdullah, R. Mardeni

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsnot available
FundersMultimedia University
KeywordsComputer scienceMiniaturizationReturn lossMicrostrip antennaPatch antennaAntenna (radio)ISM bandWirelessElectronic engineeringAntenna efficiencyElectrical engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

In wireless communication system, one of the unique challenges is the requirement for smaller and cheaper antenna design that becomes an important aspect in the deployment of wireless enabled products. To meet this challenge, we developed a simple, small, compact, low cost, and practical antenna targeted for 2.4 GHz (ISM Band) application. A detailed investigation on miniaturized microstrip planar new antenna design using a combination of proposed shorted patch and meandering method are presented. All design and simulations were done using Agilent’s Advanced Design System (ADS) Momentum. To ensure the precision, verification has been done, designs were fabricated, and measurements on return loss and impedance bandwidth were performed by using FieldFox RF Analyzer. In realizing the design, a study on the surface current is conducted by simulation in order to maintain the target resonance frequency, 2.45 GHz. The designs have resulted in 86.5% and 95.5% size reduction, in comparison with a conventional rectangular patch antenna which is used as benchmark in this work. The performance of the proposed antenna is proven to be better than other existing miniaturization techniques such as the meandered line antenna (MLA) at the same size. Further improvement on radiation characteristic is also achieved by implementing Suspended Plate Antenna (SPA) approach. From the significant size reduction obtained, the concept used in this work would be suitable for cost centric products requiring small sized wireless module.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.243
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2014
Admission routes1
Has abstractyes

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